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Intelligence platforms

Your data unified in a cloud data warehouse you own. BigQuery at the centre, SEAM as the governance layer - consistent definitions and governed metrics across your whole organisation.

What's the problem?

Your data lives in a dozen places. Your analytics tool knows about behaviour. Your CRM knows about customers. Your ad platforms know about spend. None of them talk to each other. When someone asks which marketing channels actually drive revenue, the answer takes weeks of spreadsheet wrangling - and nobody fully trusts it when it arrives.

A warehouse full of raw tables is just a more organised mess. The real unlock is governed definitions, a semantic layer everyone trusts, and the structure that turns unified data into something you can actually think with.

Ingestion, transformation and unification

Everything your organisation knows, flowing into one environment and making sense together.

  • BigQuery as your central hub
  • Marketing, product, customer and operational data connected
  • Dataform for governed, version-controlled transforms
  • Single customer view and account-based views
  • Composable CDP with privacy-compliant identity resolution
  • Data enrichment: CRM, call-centre, ad platform and third-party data joined to your first-party analytics
  • Structured and unstructured data - not just rows and columns
Check your data readiness

Control, governance and sovereignty

Your data, your infrastructure. No vendor lock-in, no renting access to your own information.

  • First-party data strategy on infrastructure you own
  • Access control, security and audit trails
  • Schema evolution and breaking change management
  • Cost optimisation as data volumes grow
  • No black boxes - everything is transparent and documented
Talk data ownership

The intelligence layer

This is what separates a warehouse from a platform. Data that understands itself - so people and AI can use it with confidence. We built SEAM to make this real: define your metrics once, and every dashboard, model and agent resolves them the same way.

  • SEAM: semantic governance that sits on top of your warehouse
  • Define metrics once in YAML - dashboards, models and agents all share them
  • One version of the truth across every team, enforced by infrastructure
  • Vertex AI and Agent Development Kit for agentic data preparation
  • Full audit trails - know what was queried, how it was resolved, and why
Learn more about SEAM

Accessibility and activation

Intelligence trapped in a warehouse is wasted. We push it into the tools and workflows where decisions happen.

  • Reverse ETL to CRM, email and ad platforms
  • Self-serve access for analysts and stakeholders
  • Enriched data powering personalisation and targeting
  • Multi-cloud connections: Snowflake, Azure, Redshift
  • The platform that dashboards, agents and models build on
Discuss your stack

What changes for you

Questions that used to take weeks get answered in minutes. Your analysts work from one governed dataset instead of stitching spreadsheets together. Dashboards are consistent. Models are reliable. Agents give trustworthy answers - because SEAM governs what they can access and how they interpret it.

And it compounds. Every new data source enriches everything that came before. Every product you build on top draws from the same foundation. Nothing starts from scratch.

Eaglemoss

11 sources unified

20+ analyst hours saved/wk

Eaglemoss had 11+ disconnected commercial and ERP sources. We unified them into a central BigQuery warehouse, automating manual reporting and saving the analysis team over 20 hours every week.

See our work →
University of Exeter

Ad to enrolment connected

Full-funnel visibility

We built a Student Recruitment Intelligence Platform connecting top-of-funnel ad impressions to SITS enrolment records. The university now has full-funnel visibility into the true ROI of every channel.

Read the full story →
Sanderson Design Group

GenAI assistant on unified data

Call volumes reduced 20%

We integrated GA4 and call-centre data in BigQuery, then built a GenAI assistant that lets the commercial team query it in natural language. The unified data revealed UX friction points that reduced call volumes by approximately 20%.

Read the full story →
Charles Stanley

Unified source of truth

Single customer view

We centralised data from two websites and two apps into BigQuery, building unified models in Dataform. This created a single customer view for personalised, consolidated reporting across the brand portfolio.

Read the full story →
Digital marketing organisation

Composable ELT architecture

87% cost reduction

A digital marketing organisation was paying £90k/year for a managed data platform. We replaced it with a composable GCP-native architecture in 10 weeks, cutting annual costs to £11k - an 87% reduction.

See our work →
Springer Nature

Siloed data integrated

Within 2% variance

Marketing, Product and Finance each worked from disconnected sources, producing conflicting numbers. We unified everything into a centralised BigQuery schema with Dataform transformations. Finance and Marketing now reconcile revenue within 2%.

Read the full story →
Springer Nature

Reporting errors reduced ~40%

Modular Dataform architecture

Multiple teams were running siloed queries and fragile pipelines. We migrated everything into modular, version-controlled Dataform models with automated data quality tests. Reporting errors dropped ~40% and analysts reclaimed 10–15 hours per week.

Read the full story →
Marqeta

Analytics built from scratch

Ongoing managed engagement

Marqeta processes billions in card transactions for the world's largest fintechs. We built their analytics foundation - GA4, GTM governance, flattened BigQuery tables, multi-source ingestion - and continue to manage it.

See our work →
BFI

E-commerce intelligence

Five revenue streams unified

BFI generates revenue from memberships, subscriptions, cinema tickets, print and merchandise - all on separate platforms. We built the tracking and data layer to unify these streams into one coherent commercial view.

See our work →
SEAM

Semantic governance for AI agents

Define once, resolve everywhere

Every platform we build needs a governance layer - consistent metric definitions, source hierarchy, entity resolution and full audit trails. SEAM is how we deliver it. Define your business logic once in YAML and every dashboard, model and agent resolves it the same way. No replatforming required.

See it in action →

How to get started

Data Readiness Assessment

Automated audit of your data maturity. Actionable output in days, not weeks.

Get assessed

GA4 to BigQuery wizard

Your GA4 data in BigQuery with governed Dataform transformations. Fast.

Try the wizard

Warehouse rescue

BigQuery instance nobody touches? We audit, restructure and bring it back to life.

Get a rescue quote

What clients say

Strategic Marketing Manager, University of Exeter

Collaborating with Measurelab has been an exceptional experience. Their team brings a depth of knowledge and technical expertise that greatly enhances our internal capabilities. They have operated as a seamless extension of our team, demonstrating professionalism, responsiveness, and a genuine commitment to delivering high-quality outcomes.

Jenna Richards - Strategic Marketing Manager, University of Exeter
From the podcast

#139 The role of AI and semantic layers in BI (with Colin Zima at Omni)

Colin Zima, CEO of Omni & Looker veteran, joins the Measure Pod to discuss revolutionising analytics by integrating AI into modern data tools.

Ready to build your intelligence platform?

Whether you need a readiness assessment or a full platform build, we'll meet you where you are.